Jingshan Lu

639 total citations
23 papers, 498 citations indexed

About

Jingshan Lu is a scholar working on Ecology, Plant Science and Global and Planetary Change. According to data from OpenAlex, Jingshan Lu has authored 23 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Ecology, 14 papers in Plant Science and 7 papers in Global and Planetary Change. Recurrent topics in Jingshan Lu's work include Remote Sensing in Agriculture (20 papers), Leaf Properties and Growth Measurement (8 papers) and Spectroscopy and Chemometric Analyses (6 papers). Jingshan Lu is often cited by papers focused on Remote Sensing in Agriculture (20 papers), Leaf Properties and Growth Measurement (8 papers) and Spectroscopy and Chemometric Analyses (6 papers). Jingshan Lu collaborates with scholars based in China, United States and Estonia. Jingshan Lu's co-authors include Yan Zhu, Weixing Cao, Tao Cheng, Yongchao Tian, Xia Yao, J. He, Xiaoqing Xu, Qi Hao, Jie Zhu and Ling Zhang and has published in prestigious journals such as Remote Sensing of Environment, Chemical Engineering Journal and Agricultural and Forest Meteorology.

In The Last Decade

Jingshan Lu

22 papers receiving 484 citations

Peers

Jingshan Lu

ECOLO

GPC

Shaoyu Han China

Kai Zhou China

Gopal Krishna India

Eatidal Amin Spain

Hamid Salehi Shahrabi Iran

Samuel Ihuoma Canada

Jiangpeng Zhu China

Isabella Mariotto United States

Dthenifer Cordeiro Santana Brazil

Luan Pierre Pott Brazil

Shaoyu Han China

Jingshan Lu

320 ×0.8

ECOLO

256 ×1.0

141 ×0.9

99 ×0.8

59 ×0.6

GPC

Citations per year, relative to Jingshan Lu Jingshan Lu (= 1×) peers Shaoyu Han

Countries citing papers authored by Jingshan Lu

Since Specialization

Citations

This map shows the geographic impact of Jingshan Lu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jingshan Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jingshan Lu more than expected).

Fields of papers citing papers by Jingshan Lu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jingshan Lu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jingshan Lu. The network helps show where Jingshan Lu may publish in the future.

Co-authorship network of co-authors of Jingshan Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Jingshan Lu. A scholar is included among the top collaborators of Jingshan Lu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jingshan Lu. Jingshan Lu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Liu, Lina, Wenjie Li, Jingshan Lu, et al.. (2025). Toxin Production by Alternaria alternata in Black Spot Disease of Chrysanthemum morifolium ‘Fubai’: Accumulation of Altenuene and Tenuazonic Acid in Flowers. Toxins. 17(4). 181–181.

Lu, Jingshan, Fadi Chen, Sumei Chen, et al.. (2025). Classification of Garden Chrysanthemum Flowering Period Using Digital Imagery from Unmanned Aerial Vehicle (UAV). Agronomy. 15(2). 421–421. 1 indexed citations

Lu, Jingshan, Sumei Chen, Fei Zhang, et al.. (2025). Machine learning-assisted hyperspectral reflectance analysis for non-destructive detection of clothianidin residues in tea chrysanthemum. Microchemical Journal. 219. 115935–115935. 1 indexed citations

Lu, Jingshan, Jan U.H. Eitel, Fadi Chen, et al.. (2025). Estimating photosynthetic traits in tea chrysanthemum using high-throughput leaf hyperspectral reflectance. Plant Physiology and Biochemistry. 221. 109606–109606. 2 indexed citations

Lu, Jingshan, Jan U.H. Eitel, Sumei Chen, et al.. (2025). High-Throughput Field Phenotyping Using Unmanned Aerial Vehicles (UAVs) for Rapid Estimation of Photosynthetic Traits. Plant Phenomics. 7(2). 100045–100045. 1 indexed citations

Zhang, Yue, Bin Gou, Yuhang Li, et al.. (2024). Integration of gel polymer electrolytes with dry electrodes for quasi-solid-state batteries. Chemical Engineering Journal. 498. 155544–155544. 3 indexed citations

Lu, Jingshan, Fadi Chen, Sumei Chen, et al.. (2024). Estimation of Garden Chrysanthemum Crown Diameter Using Unmanned Aerial Vehicle (UAV)-Based RGB Imagery. Agronomy. 14(2). 337–337. 5 indexed citations

Wu, Yin, Jingshan Lu, Fadi Chen, et al.. (2024). Monitoring the Nitrogen Nutrition Index Using Leaf-Based Hyperspectral Reflectance in Cut Chrysanthemums. Remote Sensing. 16(16). 3062–3062. 5 indexed citations

Zhu, Jie, Jingshan Lu, Wei Li, et al.. (2023). Estimation of canopy water content for wheat through combining radiative transfer model and machine learning. Field Crops Research. 302. 109077–109077. 14 indexed citations

10.

Zhu, Jie, Yuming Yin, Jingshan Lu, et al.. (2023). The relationship between wheat yield and sun-induced chlorophyll fluorescence from continuous measurements over the growing season. Remote Sensing of Environment. 298. 113791–113791. 17 indexed citations

11.

Lu, Jingshan, Yin Wu, Shuang Zhao, et al.. (2023). Estimation of plant water content in cut chrysanthemum using leaf-based hyperspectral reflectance. Scientia Horticulturae. 323. 112517–112517. 10 indexed citations

12.

Wang, Jiacheng, Ding Lu, Jingshan Lu, et al.. (2023). Grain yield prediction using multi-temporal UAV-based multispectral vegetation indices and endmember abundance in rice. Field Crops Research. 299. 108992–108992. 28 indexed citations

13.

Zheng, Hengbiao, Wenhui Wang, Jingshan Lu, et al.. (2022). Transferability of Models for Predicting Rice Grain Yield from Unmanned Aerial Vehicle (UAV) Multispectral Imagery across Years, Cultivars and Sensors. Drones. 6(12). 423–423. 12 indexed citations

14.

Lu, Jingshan, Jiancheng Song, Mengqi Wang, et al.. (2022). Estimation of nitrogen nutrition index in chrysanthemum using chlorophyll meter readings. Industrial Crops and Products. 187. 115459–115459. 7 indexed citations

15.

Lu, Jingshan, Jan U.H. Eitel, Jie Zhu, et al.. (2021). Improving Unmanned Aerial Vehicle (UAV) remote sensing of rice plant potassium accumulation by fusing spectral and textural information. International Journal of Applied Earth Observation and Geoinformation. 104. 102592–102592. 48 indexed citations

16.

Lu, Jingshan, Qi Hao, Xia Yao, et al.. (2021). Retrieving potassium levels in wheat blades using normalised spectra. International Journal of Applied Earth Observation and Geoinformation. 102. 102412–102412. 15 indexed citations

17.

Lu, Jingshan, Wanyu Li, Yong Ma, et al.. (2020). Estimation of rice plant potassium accumulation based on non-negative matrix factorization using hyperspectral reflectance. Precision Agriculture. 22(1). 51–74. 26 indexed citations

18.

Lu, Jingshan, Yan Zhu, Weixing Cao, et al.. (2019). Predicting wheat productivity: Integrating time series of vegetation indices into crop modeling via sequential assimilation. Agricultural and Forest Meteorology. 272-273. 69–80. 57 indexed citations

19.

Zhang, Ke, Xiaojun Liu, Syed Tahir Ata-Ul-Karim, et al.. (2019). Development of Chlorophyll-Meter-Index-Based Dynamic Models for Evaluation of High-Yield Japonica Rice Production in Yangtze River Reaches. Agronomy. 9(2). 106–106. 18 indexed citations

20.

Zhang, Ni, Jingshan Lu, Xia Yao, et al.. (2019). Estimating Leaf Area Index with a New Vegetation Index Considering the Influence of Rice Panicles. Remote Sensing. 11(15). 1809–1809. 47 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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